A fusion-based method for single backlit image enhancement
Qiu-Hong Wang, Xueyang Fu, Xiao-Ping Steven Zhang, Xinghao Ding · 2016
In this work, a new simple but effective fusion-based strategy for enhancing single backlit image is proposed. The fundamental idea of proposed strategy is to blend different features into a single one to improve the specific quality of image. Most of existing methods are based on the modification of histogram to enhance the contrast of low light images. However, the backlit images are different from low light images, which have wide dynamic ranges of light regions, thus the existing methods cannot achieve good enhanced results of backlit images. To improve performance of enhanced results, the proposed method considers numerous features of images and processes the dark and bright regions, respectively. Furthermore, proposed method introduces weight maps to increase the visibility. Experimental results show that proposed method is superior to existing methods, which achieves better results both in visual effects and processing time.